Category Data & Analytic Specialist for Retail
JOB DESCRIPTION:
Category Data & Analytic Specialist for Retail
About Abbott
Abbott is a global healthcare leader, creating breakthrough science to improve people’s health. We’re always looking towards the future, anticipating changes in medical science and technology.
Working at Abbott
At Abbott, you can do work that matters, grow, and learn, care for yourself and family, be your true self and live a full life. You will have access to:
- Career development with an international company where you can grow the career you dream of .
- A company recognized as a great place to work in dozens of countries around the world and named one of the most admired companies in the world by Fortune.
- A company that is recognized as one of the best big companies to work for as well as a best place to work for diversity, working mothers, female executives, and scientists.
The Opportunity
This position works out of our Mexico City location in the Pharmaceutical Division. We are committed to bringing the benefits of our trusted medicines to more people in the world’s fastest-growing countries. Our broad portfolio of high-quality and differentiated branded generic medicines reaches across multiple therapeutic areas including gastroenterology, women's health, cardiometabolic, pain management/central nervous system, and respiratory.
As the Category Data & Analytic Specialist for Retail, you’ll be responsible of design, develop, and maintain end-to-end data and analytics solutions that enable strategic decision-making across Sales, Marketing, Field Force, and Market Research organizations. The role is responsible for building scalable data infrastructure, automating information workflows, developing analytical models, and delivering actionable insights that improve commercial performance, product availability, and operational efficiency.
What You’ll Do:
- Design, develop, and administer enterprise data models and Data Warehouses within Microsoft Fabric, ensuring data quality, scalability, and availability.
- Build, maintain, and monitor automated ETL/ELT pipelines integrating data from multiple internal and external sources.
- Develop and optimize Power BI dashboards and reporting solutions to support commercial, inventory, and customer performance management.
- Develop analytical models and forecasting solutions to improve inventory planning, reduce stockouts, and minimize backorder risks.
- Implement automation, NLP, and AI-driven solutions to improve operational efficiency and eliminate manual processes.
- Conduct geospatial analyses and location-based insights to support commercial strategy and field force effectiveness.
- Partner with cross-functional stakeholders to translate business needs into scalable data solutions and actionable insights.
- Research emerging technologies,
- AI capabilities, and analytics tools, leading proof-of-concept initiatives to drive innovation.
Required Qualifications
- Bachelor’s degree
- Strong understanding of data modeling, analytics, reporting, business intelligence, data integration, and process automation. Ability to translate business requirements into scalable and sustainable data solutions.
- Any industry-specific experience needed: 0-2 years of experience in Data Analytics, Business Intelligence, Data Engineering, Automation, or related disciplines.
Advanced SQL and Python.
Microsoft Fabric and Power BI.
Azure Data Platform.
ETL/ELT development and dimensional modeling.
Git and version control.
Intermediate to advanced English proficiency.
Desirable: NLP, Machine Learning, Forecasting (ARIMA), Geospatial Analytics, Linux.
Follow your career aspirations to Abbott for diverse opportunities with a company that can help you build your future and live your best life. Abbott is an Equal Opportunity Employer, committed to employee diversity.
Connect with us at www.abbott.com, on Facebook at www.facebook.com/Abbott and on Twitter @AbbottNews and @AbbottGlobal.
The base pay for this position is
N/AIn specific locations, the pay range may vary from the range posted.